Application Relevance Ranking via Composite Importance and Urgency
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Solution Overview
Problem
Employees face challenges in managing and prioritizing numerous task-specific applications as their job responsibilities expand, leading to difficulties in tracking relevant applications and tasks across different projects and roles.
Innovation Solution
A method to determine user-specific relevance of applications by calculating composite importance and urgency values based on various parameters, such as due dates, role, location, and usage patterns, and displaying a graphical representation to prioritize applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If employees use more task-specific applications to handle expanded job responsibilities, then productivity and capability are improved, but device complexity and difficulty of tracking applications increase
Solution Approach 1:
The patent introduces a relevance determination system as an intermediary between the employee and multiple applications. This system automatically calculates relevance values by analyzing importance parameters (such as task criticality, business impact) and urgency parameters (such as deadlines, time sensitivity), then presents a prioritized ranking. This mediator eliminates the need for employees to manually track and prioritize numerous applications, resolving the complexity issue while maintaining expanded capability.
Solution Approach 2:
The system performs self-service by automatically determining application relevance without requiring employee intervention. The relevance determination system independently analyzes application data, calculates importance and urgency values, and generates prioritized rankings. This automation frees employees from the manual burden of tracking applications while their expanded job capabilities remain supported through the appropriate applications.
2Loss of information
If employees manually track multiple applications and tasks, then application awareness is improved, but time consumption and productivity are reduced
Solution Approach 1:
The system continuously monitors application data and provides feedback in the form of updated relevance rankings. Importance parameters and urgency parameters are automatically collected from applications, processed through the relevance determination system, and presented as actionable prioritized lists. This feedback mechanism keeps employees informed about application status without requiring manual tracking, eliminating time loss while maintaining comprehensive application awareness.
Solution Approach 2:
The relevance determination system performs self-service by automatically collecting, analyzing, and ranking application relevance without employee time investment. The system independently processes importance and urgency parameters, calculates relevance values, and presents prioritized recommendations. This automation eliminates the time employees would otherwise spend manually tracking applications while maintaining full application awareness through the system's continuous monitoring.
3Ease of operation
If traditional monolithic applications are used, then ease of operation is improved, but adaptability to specific tasks and roles decreases
Solution Approach 1:
The patent applies segmentation by dividing monolithic applications into separate task-specific applications. Each application is optimized for a particular function or task, allowing employees to use only the relevant application for each specific task rather than navigating through a large monolithic system. The relevance determination system then segments the prioritization process by analyzing individual applications based on their specific task requirements, improving both usability and adaptability.
Solution Approach 2:
The system implements local quality by tailoring the relevance determination to each specific application based on its unique characteristics and task requirements. Importance and urgency parameters are evaluated locally for each application, with relevance calculations adjusted according to the specific task context, user role, and application functionality. This localized approach allows task-specific applications to maintain high usability while adapting to different roles and tasks through the personalized relevance ranking.
Data Source
AI summary
The subject matter disclosed herein provides methods for determining the user-specific relevance of various applications and displaying a graphical representation of these relevance values. The method may receive information from one or more applications installed on a device. This information may include importance parameters, importance parameter values, urgency parameters, and urgency parameter values associated with each application. A composite importance value and a composite urgency value may be determined for each application. A relevance value may be determined for each application based on the composite importance value and composite urgency value. A graphical representation of the relevance of each application may be displayed on the device. Related apparatus, systems, techniques, and articles are also described.